Search results for: negative emotion
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4841

Search results for: negative emotion

4781 Emotion Recognition Using Artificial Intelligence

Authors: Rahul Mohite, Lahcen Ouarbya

Abstract:

This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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4780 The Emotional Experience of Urban Ruins and the Exploration of Urban Memory

Authors: Yan Jia China

Abstract:

The ruins is a kind of historical intention, which is also the current real existence of developing city. Zen culture of ancient China has a profound esthetic emotion, similarly, the west establish the concept of aesthetics of relic along with the Romanism’s (such as Rousseau etc.) sentiment to historical ruins at the end of 18th century. Nowadays, with the decline of traditional industrial society as well as the rise of post-industrial age, contemporary society must face the ruins and garbage problem which is left by industrial society. Commencing from the perspective of emotion and memory, this paper analyzes the importance for emotional needs as well as their existing status of several projects, such as the Capital Steelworks in Beijing (industrial devastation), the Shibati old section in Chongqing (urban slums) and the Old Hurva Synagogue in Jerusalem (ruins of war). It emphasizes urban design which is started from emotion and the sustainable development of city memory through managing the urban ruins which is criticized by people with the perspective of ecology and art.

Keywords: cultural heritage, urban ruins, ecology, emotion, sustainable urban memory

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4779 Personality Moderates the Relation Between Mother´s Emotional Intelligence and Young Children´s Emotion Situation Knowledge

Authors: Natalia Alonso-Alberca, Ana I. Vergara

Abstract:

From the very first years of their life, children are confronted with situations in which they need to deal with emotions. The family provides the first emotional experiences, and it is in the family context that children usually take their first steps towards acquiring emotion knowledge. Parents play a key role in this important task, helping their children develop emotional skills that they will need in challenging situations throughout their lives. Specifically, mothers are models imitated by their children. They create specific spatial and temporal contexts in which children learn about emotions, their causes, consequences, and complexity. This occurs not only through what mothers say or do directly to the child. Rather, it occurs, to a large extent, through the example that they set using their own emotional skills. The aim of the current study was to analyze how maternal abilities to perceive and to manage emotions influence children’s emotion knowledge, specifically, their emotion situation knowledge, taking into account the role played by the mother’s personality, the time spent together, and controlling the effect of age, sex and the child’s verbal abilities. Participants were 153 children from 4 schools in Spain, and their mothers. Children (41.8% girls)age range was 35 - 72 months. Mothers (N = 140) age (M = 38.7; R = 27-49). Twelve mothers had more than one child participating in the study. Main variables were the child´s emotion situation knowledge (ESK), measured by the Emotion Matching Task (EMT), and receptive language, using the Picture Vocabulary Test. Also, their mothers´ Emotional Intelligence (EI), through the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT) and personality, with The Big Five Inventory were analyzed. The results showed that the predictive power of maternal emotional skills on ESK was moderated by the mother’s personality, affecting both the direction and size of the relationships detected: low neuroticism and low openness to experience lead to a positive influence of maternal EI on children’s ESK, while high levels in these personality dimensions resulted in a negative influence on child´s ESK. The time that the mother and the child spend together was revealed as a positive predictor of this EK, while it did not moderate the influence of the mother's EI on child’s ESK. In light of the results, we can infer that maternal EI is linked to children’s emotional skills, though high level of maternal EI does not necessarily predict a greater degree of emotionknowledge in children, which seems rather to depend on specific personality profiles. The results of the current study indicate that a good level of maternal EI does not guarantee that children will learn the emotional skills that foster prosocial adaptation. Rather, EI must be accompanied by certain psychological characteristics (personality traits in this case).

Keywords: emotional intelligence, emotion situation knowledge, mothers, personality, young children

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4778 Generating Music with More Refined Emotions

Authors: Shao-Di Feng, Von-Wun Soo

Abstract:

To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.

Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning

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4777 Exploring Fear in Moral Life: Implications for Education

Authors: Liz Jackson

Abstract:

Fear is usually considered as a basic emotion. In society, it is normally cast as undesirable, but also as partly unavoidable. Fear can be said to underlie courage or be required for courage, or it can be understood as its foil. Fear is not normally promoted (intentionally) in education, or treated as something that should be cultivated in schools or in society. However, fear is a basic, to some extent unavoidable emotion, related to truly fearsome things in the world. Fear is also understood to underlie anxiety. Fear is seen as basically disruptive to education, while from a psychological view it is an ordinary state. that cannot be avoided altogether. Despite calls to diminish this negative and mixed feeling in education and society, it can be regarded as socially and personally valuable, and psychologically functional in some situations. One should not take for granted the goodness of fear. However, it can be productive to explore its moral worth, and uses and abuses. Such uncomfortable feelings and experiences can be cultivated and explored via educational and other societal influences, in ways that can benefit a person and their relations with others in the world, while they can also be detrimental.

Keywords: virtue ethics, philosophy of education, moral philosophy, fear

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4776 The Impact of Online Games, Massively Multiplayer Online Game towards Undergraduate Students in Malaysia

Authors: Rubijesmin Abdul Latif, Norshakirah Abdul Aziz, Mohd Taufik Abdul Jalil

Abstract:

This paper focuses on the impact of online games among Malaysian undergraduate students. The purpose of this study is to investigate whether online games (especially MMOGs) impacted students positively or vice versa; focusing on three elements (time management, social life, and emotion). A total of 83 respondents comprised from 14 Malaysia universities, randomly selected undergraduate students who play MMOGs (casual and hardcore gamers i.e. addiction to MMOGs) were involved in this study. The results showed that MMOGs have only negative impact on students capabilities in time management, meanwhile as for the elements social life and emotion, MMOGs do not affect them negatively.

Keywords: internet game addiction, online games, MMOGs, impact, undergraduate students

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4775 Factors That Affect the Mental Health Status of Syrian Refugee Girls in Post-Resettlement Context

Authors: Vivian Khamis

Abstract:

Exposure to war and forced migration have been widely linked to child subsequent adaptation. What remains sparse is research spanning multiple risk and protective factors and examining their unique and relative implications to difficulties in mental health among refugee girls. This study investigated the mechanisms through which posttraumatic stress disorder (PTSD), emotion dysregulation , neuroticism, and behavioral and emotional disorders in Syrian refugee girls is impacted by exposure to war traumas, age, and other risk and protective factors such as coping styles, family relationships, and school environment. The sample consisted of 539 Syrian refugee girls who ranged in age from 7 to 18 years attending public schools in various governorates in Lebanon and Jordan. Two school counselors carried out the interviews with children at school. Results indicated that war trauma, older age, and a combination of negative copying style associated with conflict in the family could lead to an overall state of emotion dysregulation, neuroticism, behavioral and emotional disorders, and PTSD in refugee girls. On the other hand, lapse of time since resettlement in host country, positive copying style, cohesion, and expressiveness in the family would lead to more positive mental health status, including lower levels of emotion dysregulation, neuroticism, behavioral and emotional disorders, and PTSD . Enhanced understanding of the mechanistic role of risk and protective factors in contributing to difficulties in mental health in refugee girls may contribute to the development of effective interventions to target the psychological effects of the refugee experience.

Keywords: refugee girls, PTSD, emotion dysregulation, neuroticism, behavioral and emotional disorders

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4774 Composite Kernels for Public Emotion Recognition from Twitter

Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

Abstract:

The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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4773 Multimodal Database of Emotional Speech, Video and Gestures

Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

Abstract:

People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech

Procedia PDF Downloads 322
4772 Speech Detection Model Based on Deep Neural Networks Classifier for Speech Emotions Recognition

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

Abstract:

Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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4771 Ahmad Sabzi Balkhkanloo, Motahareh Sadat Hashemi, Seyede Marzieh Hosseini, Saeedeh Shojaee-Aliabadi, Leila Mirmoghtadaie

Authors: Elyria Kemp, Kelly Cowart, My Bui

Abstract:

According to the National Institute of Mental Health, an estimated 31.9% of adolescents have had an anxiety disorder. Several environmental factors may help to contribute to high levels of anxiety and depression in young people (i.e., Generation Z, Millennials). However, as young people negotiate life on social media, they may begin to evaluate themselves using excessively high standards and adopt self-perfectionism tendencies. Broadly defined, self-perfectionism involves very critical evaluations of the self. Perfectionism may also come from others and may manifest as socially prescribed perfectionism, and young adults are reporting higher levels of socially prescribed perfectionism than previous generations. This rising perfectionism is also associated with anxiety, greater physiological reactivity, and a sense of social disconnection. However, theories from psychology suggest that improvement in emotion regulation can contribute to enhanced psychological and emotional well-being. Emotion regulation refers to the ways people manage how and when they experience and express their emotions. Cognitive reappraisal and expressive suppression are common emotion regulation strategies. Cognitive reappraisal involves changing the meaning of a stimulus that involves construing a potentially emotion-eliciting situation in a way that changes its emotional impact. By contrast, expressive suppression involves inhibiting the behavioral expression of emotion. The purpose of this research is to examine the efficacy of social marketing initiatives which promote emotion regulation strategies to help young adults regulate their emotions. In Study 1 a single factor (emotional regulation strategy: a cognitive reappraisal, expressive, control) between-subjects design was conducted using an online, non-student consumer panel (n=96). Sixty-eight percent of participants were male, and 32% were female. Study participants belonged to the Millennial and Gen Z cohort, ranging in age from 22 to 35 (M=27). Participants were first told to spend at least three minutes writing about a public speaking appearance which made them anxious. The purpose of this exercise was to induce anxiety. Next, participants viewed one of three advertisements (randomly assigned) which promoted an emotion regulation strategy—cognitive reappraisal, expressive suppression, or an advertisement non-emotional in nature. After being exposed to one of the ads, participants responded to a measure composed of two items to access their emotional state and the efficacy of the messages in fostering emotion management. Findings indicated that individuals in the cognitive reappraisal condition (M=3.91) exhibited the most positive feelings and more effective emotion regulation than the expressive suppression (M=3.39) and control conditions (M=3.72, F(1,92) = 3.3, p<.05). Results from this research can be used by institutions (e.g., schools) in taking a leadership role in attacking anxiety and other mental health issues. Social stigmas regarding mental health can be removed and a more proactive stance can be taken in promoting healthy coping behaviors and strategies to manage negative emotions.

Keywords: emotion regulation, anxiety, social marketing, generation z

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4770 The Role of Cognitive Control and Social Camouflage Associated with Social Anxiety Autism Spectrum Conditions

Authors: Siqing Guan, Fumiyo Oshima, Eiji Shimizu, Nozomi Tomita, Toru Takahashi, Hiroaki Kumano

Abstract:

Risk factors for social anxiety in autism spectrum conditions involve executive attention, emotion regulation, and thought regulation as processes of cognitive dysregulation. Social camouflaging behaviors as strategies used to mask and/or compensate for autism characteristics during social interactions in autism spectrum conditions have also been emphasized. However, the role of cognitive dysregulation and social camouflaging related to social anxiety in autism spectrum conditions has not been clarified. Whether these factors are specific to social anxiety in autism spectrum conditions or common to social anxiety independent of autism spectrum conditions needs to be clarified. Here, we explored risk factors specific to social anxiety in autism spectrum conditions and general risk factors for social anxiety independent of autism spectrum conditions. From the Japanese participants in early adulthood (age=18~39) of the online survey in Japan, those who exceeded the Japanese version Autism-Spectrum Quotient cutoff (33 points or more )were divided into the autism spectrum conditions group (ASC; N=255, mean age=32.08, SD age=5.16)and those who did not exceed the cutoff were divided into the non-autism spectrum conditions group (Non-ASC; N=255, mean age=31.70, SD age=5.09). Using the Japanese versions of the Social Phobia Scale, the Social Interaction Anxiety Scale, and the Short Fear of Negative Evaluation Scale, a composite score for social anxiety was calculated using a method of principal. We also measured emotional control difficulties using the Difficulties in Emotion Regulation Scale, executive attention using the Effortful Control Scale for Adults, rumination using the Rumination-Reflection Questionnaire, and worry using the Penn State Worry Questionnaire. This study was passed through the review of the Ethics Committee. No conflicts of interest. Multiple regression analysis with forced entry method was used to predict social anxiety in the ASC and non-ASC groups separately, based on executive attention, emotion dysregulation, worry, rumination, and social camouflage. In the ASC group, emotion dysregulation (β=.277, p<.001), worry (β=.162, p<.05), assimilation (β=.308, p<.001) and masking (β=.275, p<.001) were significant predictors of social anxiety (F (7,247) = 45.791, p <.001, R2=.565). In the non-ASC groups,emotion dysregulation (β=.171, p<.05), worry (β=.344,p <.001), assimilation (β=.366,p <.001) and executive attention (β=-.132,p <.05) were significant predictors of social anxiety (F (7,207) =47.333, p <.001, R2=.615).The findings suggest that masking was shown to be a risk factor for social anxiety specific to autism spectrum conditions, while emotion dysregulation, worry, and assimilation were shown to be common risk factors for social anxiety, regardless of autism spectrum conditions. In addition, executive attention is a risk factor for social anxiety without autism spectrum conditions.

Keywords: autism spectrum, cognitive control, social anxiety, social camouflaging

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4769 Emotion Motives Predict the Mood States of Depression and Happiness

Authors: Paul E. Jose

Abstract:

A new self-report measure named the General Emotion Regulation Measure (GERM) assesses four key goals for experiencing broad valenced groups of emotions: 1) trying to experience positive emotions (e.g., joy, pride, liking a person); 2) trying to avoid experiencing positive emotions; 3) trying to experience negative emotions (e.g., anger, anxiety, contempt); and 4) trying to avoid experiencing negative emotions. Although individual differences in GERM motives have been identified, evidence of validity with common mood outcomes is lacking. In the present study, whether GERM motives predict self-reported subjective happiness and depressive symptoms (CES-D) was tested with a community sample of 833 young adults. It was predicted that the GERM motive of trying to experience positive emotions would positively predict subjective happiness, and analogously trying to experience negative emotions would predict depressive symptoms. An initial path model was constructed in which the four GERM motives predicted both subjective happiness and depressive symptoms. The fully saturated model included three non-significant paths, which were subsequently pruned, and a good fitting model was obtained (CFI = 1.00; RMR = .007). Two GERM motives significantly predicted subjective happiness: 1) trying to experience positive emotions ( = .38, p < .001) and 2) trying to avoid experiencing positive emotions ( = -.48, p <.001). Thus, individuals who reported high levels of trying to experience positive emotions reported high levels of happiness, and individuals who reported low levels of trying to avoid experiencing positive emotions also reported high levels of happiness. Three GERM motives significantly predicted depressive symptoms: 1) trying to avoid experiencing positive emotions ( = .20, p <.001); 2) trying to experience negative emotions ( = .15, p <.001); and 3) trying to experience positive emotions (= -.07, p <.001). In agreement with predictions, trying to experience positive emotions was positively associated with subjective happiness and trying to experience negative emotions was positively associated with depressive symptoms. In essence, these two valenced mood states seem to be sustained by trying to experience similarly valenced emotions. However, the three other significant paths in the model indicated that emotional motives play a complicated role in supporting both positive and negative mood states. For subjective happiness, the GERM motive of not trying to avoid positive emotions, i.e., not avoiding happiness, was also a strong predictor of happiness. Thus, people who report being the happiest are those individuals who not only strive to experience positive emotions but also are not ambivalent about them. The pattern for depressive symptoms was more nuanced. Individuals who reported higher depressive symptoms also reported higher levels of avoiding positive emotions and trying to experience negative emotions. The strongest predictor for depressed mood was avoiding positive emotions, which would suggest that happiness aversion or fear of happiness is an important motive for dysphoric people. Future work should determine whether these patterns of association are similar among clinically depressed people, and longitudinal data are needed to determine temporal relationships between motives and mood states.

Keywords: emotions motives, depression, subjective happiness, path model

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4768 Effect of Positive Psychology (PP) Interventions on College Students’ Well-Being, Career Stress and Coronavirus Anxiety

Authors: Erva Kaygun

Abstract:

The purpose of this research is to investigate the effects of positive psychology interventions on college students' positive-negative emotions, coronavirus anxiety, and career stress. 4 groups of college students are compared in terms of the level of exposure to PP constructs ( Non-Psychology, Psychology, Positive Psychology Course, and Positive Psychology Boot Camp). In this research, Pearson Correlation, independent t-tests, ANOVA, and Post-Hoc tests are conducted. Without being significant, the groups exposed to PP constructs showed higher positive emotions and total PERMA scores, whereas negative emotions, career stress, and coronavirus stress remained similar. It is crucial to indicate that career stress is higher among all psychology students when compared to non-psychology students. The results showed that the highest exposure group (PP Boot Camp) showed no difference in negative emotions, whereas higher PERMA scores and positive emotion scores were on the Positive and Negative Affect Schedule (PANAS) scale.

Keywords: positive psychology, college students, well being, anxiety

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4767 Feeling Ambivalence Towards Values

Authors: Aysheh Maslemani, Ruth Mayo, Greg Maio, Ariel Knafo-Noam

Abstract:

Values are abstract ideals that serve as guiding principles in one's life. As inherently positive and desirable concepts, values are seen as motivators for actions and behaviors. However, research has largely ignored the possibility that values may elicit negative feelings despite being explicitly important to us. In the current study, we aim to examine this possibility. Four hundred participants over 18 years(M=41.6, SD=13.7, Female=178) from the UK completed a questionnaire in which they were asked to indicate their level of positive/negative feelings towards a comprehensive list of values and then report the importance of these values to them. The results support our argument by showing that people can have negative feelings towards their values and that people can feel both positive and negative emotions towards their values simultaneously, which means feeling ambivalence. We ran a mixed-effect model with ambivalence, value type, and their interaction as fixed effects, with by subject random intercept and by subject random slope for ambivalence. The results reveal that values that elicit less ambivalence predicted higher ratings for value importance. This research contributes to the field of values on multiple levels. Theoretically, it will uncover new insights about values, such as the existence of negative emotions towards them and the presence of ambivalence towards values. These findings may inspire future studies to explore the effects of ambivalence on people's well-being, behaviors, cognition, and their affect. We discuss the findings and consider their implications for understanding the social psychological mechanisms underpinning value ambivalence.

Keywords: emotion, social cognition, values., ambivalence

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4766 Feeling Ambivalence Towards Yours Values

Authors: Aysheh Maslemani, Ruth Mayo, Greg Maio, Ariel Knafo-Noam

Abstract:

Values are abstract ideals that serve as guiding principles in one's life. As inherently positive and desirable concepts, values are seen as motivators for actions and behaviors. However, research has largely ignored the possibility that values may elicit negative feelings despite being explicitly important to us. In the current study we aim to examine this possibility. Four hundred participants over 18 years(M=41.6,SD=13.7,Female=178) from the UK completed a questionnaire in which they were asked to indicate their level of positive/negative feelings towards a comprehensive list of values and then report the importance of these values to them. The results support our argument by showing that people can have negative feelings towards their values and that people can feel both positive and negative emotions towards their values simultaneously, which means feeling ambivalence. We ran a mixed-effect model with ambivalence, value type, and their interaction as fixed effects, with by subject random intercept, and by subject random slope for ambivalence. The results reveal that values that elicit less ambivalence predicted higher ratings for value importance. This research contributes to the field of values on multiple levels. Theoretically, it will uncover new insights about values, such as the existence of negative emotions towards them, the presence of ambivalence towards values. These findings may inspire future studies to explore the effects of ambivalence on people's well-being, behaviors, cognition, and their affect. We discuss the findings and consider their implications for understanding the social psychological mechanisms underpinning value ambivalence.

Keywords: ambivalence, emotion, social cognition, values

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4765 The Effectiveness of Conflict Management of Factories' Employee in Thailand

Authors: Pacharaporn Lekyan

Abstract:

The purpose of this study is to explore the conflict management affecting the workplace and analyze the ability of the prediction of leadership of the headman and the methods to handle the conflict in an organization. The quantitative research and developed the questionnaire in order to collect information from the respondents from 200 samples from leader or manager who worked in frozen food factories in Thailand. The result analysis shows about the problem of the relationship between conflict management factors, leadership, and the confliction in organization. The emotion of the leader in the organization is not the only factor that can affect conflict management but also the emotion of surrounding people which this factor can happen all the time and shows that four out of five factors of interpersonal conflict management have affected on emotion intelligence and also shows that the behaviors of leadership have an influence on conflict management.

Keywords: conflict management, emotional intelligence, leadership, factories' employee

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4764 When and Why Unhappy People Avoid Enjoyable Experiences

Authors: Hao Shen, Aparna Labroo

Abstract:

Across four studies, we show people in a negative mood avoid anticipated enjoyable experiences because of the subjective difficulty in simulating those experiences, and they misattribute these feelings of difficulty to reduced pleasantness of the anticipated experience. We observe the avoidance of enjoyable experiences only for anticipated experiences that involve smile-like facial-muscular simulation. When the need for facial-muscular simulation is attenuated, or when the anticipated experience relies on facial-muscular simulation to a lesser extent, people in a negative mood no longer avoid enjoyable experiences, but rather seek such experiences because they fit better with their ongoing mood-repair goals.

Keywords: emotion regulation, mood repair, embodiment, anticipated experiences

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4763 Analysis of Nonlinear and Non-Stationary Signal to Extract the Features Using Hilbert Huang Transform

Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

Abstract:

It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

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4762 Developing an AI-Driven Application for Real-Time Emotion Recognition from Human Vocal Patterns

Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

Abstract:

This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal pattern

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4761 Individualized Emotion Recognition Through Dual-Representations and Ground-Established Ground Truth

Authors: Valentina Zhang

Abstract:

While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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4760 Emotion Recognition with Occlusions Based on Facial Expression Reconstruction and Weber Local Descriptor

Authors: Jadisha Cornejo, Helio Pedrini

Abstract:

Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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4759 A Study on the Ideal and Actual Coping Responses of Public and Private College School Teachers on Job-Related Stress

Authors: Zaralyn Bernardo, Dante Boac, Annabelle Del Rosario

Abstract:

Professional individuals who are in a primary role to impart learning with the new generation are alarmingly tend to have a vast decrease in their workforce due to stress at work. Thus, the study used mixed method research design to explore the ideal and actual coping patterns of college school teachers, both private and public, using Coping Response Inventory-Adult (CRI-Adult). It was suggested that in order for coping to be effective there must be a congruence or good match between coping efforts and preferred coping style. Results basically provided the same information on sources of teacher stress. However, workload and low salary were more likely heightened, for public and private school, respectively. There is also a significant difference between the ideal and actual coping style of college school teachers. Though the public school teachers leaned towards problem-focused as their ideal way of coping, both public and private teachers are somewhat inclined to use emotion-focused coping in actual situation. Results of FGD identified the factors that contribute to the incongruence or mismatch in their preferred style of coping and actual efforts to cope. Identified factors based on thematic analysis (TA) are clustered into themes such as affectivity and rehearsal of the preferred coping responses, sensitivity to pressure impairs coping efficacy, seeking for social acceptance and approval, indefinite appraisal of perceived stress, emotional dysregulation, and impulsivity, immediate desire to terminate negative emotion and adversity. Most of the factors somewhat provide partial elucidation on the engagement of the respondents on emotion-focused coping.

Keywords: coping responses subtypes, appraisal, teacher stress, ideal and actual coping

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4758 Exploring Subjective Simultaneous Mixed Emotion Experiences in Middle Childhood

Authors: Esther Burkitt

Abstract:

Background: Evidence is mounting that mixed emotions can be experienced simultaneously in different ways across the lifespan. Four types of patterns of simultaneously mixed emotions (sequential, prevalent, highly parallel, and inverse types) have been identified in middle childhood and adolescence. Moreover, the recognition of these experiences tends to develop firstly when children consider peers rather than the self. This evidence from children and adolescents is based on examining the presence of experiences specified in adulthood. The present study, therefore, applied an exhaustive coding scheme to investigate whether children experience types of previously unidentified simultaneous mixed emotional experiences. Methodology: One hundred and twenty children (60 girls) aged 7 years 1 month - 9 years 2 months (X=8 years 1 month; SD = 10 months) were recruited from mainstream schools across the UK. Two age groups were formed (youngest, n = 61, 7 years 1 month- 8 years 1 months: oldest, n = 59, 8 years 2 months – 9 years 2 months) and allocated to one of two conditions hearing vignettes describing happy and sad mixed emotion events in age and gender-matched protagonist or themselves. Results: Loglinear analyses identified new types of flexuous, vertical, and other experiences along with established sequential, prevalent, highly parallel, and inverse types of experience. Older children recognised more complex experiences other than the self-condition. Conclusion: Several additional types of simultaneously mixed emotions are recognised in middle childhood. The theoretical relevance of simultaneous mixed emotion processing in childhood is considered, and the potential utility of the findings in emotion assessments is discussed.

Keywords: emotion, childhood, self, other

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4757 Documents Emotions Classification Model Based on TF-IDF Weighting Measure

Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

Abstract:

Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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4756 The Effectiveness of Group Counseling of Mindfulness-Based Cognitive Therapy on Cognitive Emotion Regulation in High School Students

Authors: Hossein Ilanloo, Sedigheh Ahmadi, Kianoosh Zahrakar

Abstract:

The present study aims at investigating the effectiveness of group counseling of mindfulness-based cognitive therapy on cognitive emotion regulation in high school students. The research design was quasi-experimental and pre-test-post-test type and a two-month follow-up with a control group. The statistical population of the study consisted of all-male high school students in Takestan city in the Academic Year 2020-2021. The sample comprised 30 high school male students selected through the convenience sampling method and randomly assigned to experimental (n=15) and control (n=15) groups. The experimental group then received ten sessions of 90-minute group counseling of mindfulness-based cognitive therapy, and the control group did not receive any intervention. In order to collect data, the author used the Cognitive Emotion Regulation Questionnaire (CERQ). The researcher also used multivariate analysis of covariance, repeated measures, LSD post hoc test, and SPSS-26 software for data analysis.

Keywords: mindfulness-based cognitive therapy, cognitive emotion regulation, students, high schools

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4755 Internet Impulse Buying: A Study Based on Stimulus-Organism-Response Theory

Authors: Pui-Lai To, Yi-Jing Tsai

Abstract:

As the advance of e-commerce technologies, the consumers buying behavior have changed. The focus on consumer buying behavior has already shifted from physical space to the cyberspace, which impulse buying is a major issue of concern. This study examines the stimulus effect of web environment on the consumer's emotional states, and in turn, affecting the urge of impulse buying based on a stimulus-organism-response (S-O-R) theory. Website ambiance and website service quality are the two stimulus variables. The study also explores the effects and the moderator effects of contextual variables and individual characteristic variables on the web environment, the emotional states and the urge of impulse buying. A total of 328 valid questionnaires were collected. Structural equation modeling was used to test the research hypothesis. This study found that both website ambiance and website service quality have a positive effect on consumer emotion, which in turn positively affect the urge of impulse buying. Consumer’s trait of impulse buying has a positive effect on the urge of impulse buying. Consumer’s hedonic motivation has a positive effect on both emotion state and the urge of impulse buying. On the other hand, the study found that money available for the consumer would positively affect consumer's emotion state and time available for the consumer would negatively affect the relationship between website service quality and consumer emotion. The result of this study validates Internet impulse buying behavior based on the S-O-R theory. This study also suggests that having a good website atmosphere and service quality is important to influencing consumers’ emotion and increasing the likelihood of consumer purchasing. The study could serve as a basis for the future research regarding online consumer behavior.

Keywords: emotion state, impulse buying, stimulus-organism-response, the urge of impulse buying

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4754 Facial Emotion Recognition with Convolutional Neural Network Based Architecture

Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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4753 Feeling Bad May Not Make You Behave Unethically! Lessons Learned From the 2022 Shanghai COVID-19 Lockdown

Authors: Zeren Li, Wenkai Song

Abstract:

Shanghai experienced a 3-month lockdown in 2022. This unprecedented lockdown made local residents afraid, anxious and worried about the unpredictability of the future. During the lockdown, many unethical behaviors related to lockdown are noticed by the public. Our studies documented unethical behavior during this lockdown by moral hypocrisy and moral justification examined whether or not the lockdown makes people behave more unethically, and analyzed the relationship between negative emotions and unethical behavior. In Study 1, we recruited 240 participants from Shanghai (n = 120) and other cities (n = 120) to compare people in lockdown and non-lockdown areas. Surprisingly, we found that people in lockdown areas tend to behave more ethically, exhibiting less moral hypocrisy. In addition, residents of the lockdown area have significantly higher negative emotions (afraid, nervousness, upset, and feelings of uncertainty). In Study 2, we recruited 70 respondents from Shanghai and found that people behave relatively ethically in lockdown-related scenarios (negatively correlated with anxiety about the lockdown) with relatively less moral justification than in lockdown-unrelated scenarios. We propose that negative emotions may reduce unethical behavior that may exacerbate the causes (in our study, the lockdown) of these negative emotions. Experiments may help to establish the causal relationship and verify the model in future research.

Keywords: COVID-19, unethical behavior, emotion, anxiety, moral justification, moral hypocrisy, China

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4752 The Neuropsychology of Autism and ADHD

Authors: Anvikshaa Bisen, Krish Makkar

Abstract:

Professionals misdiagnose autism by ticking off symptoms on a checklist without questioning the causes of said symptoms, and without understanding the innate neurophysiology of the autistic brain. A dysfunctional cingulate gyrus (CG) hyperfocuses attention in the left frontal lobe (logical/analytical) with no ability to access the right frontal lobe (emotional/creative), which plays a central role in spontaneity, social behavior, and nonverbal abilities. Autistic people live in a specialized inner space that is entirely intellectual, free from emotional and social distractions. They have no innate biological way of emotionally connecting with other people. Autistic people process their emotions intellectually, a process that can take 24 hours, by which time it is too late to have felt anything. An inactive amygdala makes it impossible for autistic people to experience fear. Because they do not feel emotion, they have no emotional memories. All memories are of events that happened about which they felt no emotion at the time and feel no emotion when talking about it afterward.

Keywords: autism, Asperger, Asd, neuropsychology, neuroscience

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